Robotic vacuum cleaners are known in the art. In general robotic vacuum cleaners are equipped with a drive arrangement in the form of a motor for moving the cleaner across a surface to be cleaned. The robotic vacuum cleaners are further equipped with intelligence in the form of microprocessor(s) and navigation means for causing an autonomous behaviour such that the robotic vacuum cleaners can freely move around and clean a space or area in the form of e.g. a room.
In many fields of technology, it is desirable to use robots with an autonomous behaviour such that they can freely move around a space without colliding with possible obstacles and walls or the like, which limit a perimeter of a room.
As an a example, robotic vacuum cleaners exist in the art with the capability of more or less autonomously vacuum cleaning a room in which furniture such as tables and chairs and other obstacles such as walls and stairs are located. Traditionally, these robotic vacuum cleaners have navigated a room by means of using e.g. ultrasound or light waves or laser beams. These means of ultrasound, light waves or laser beams enable the robotic vacuum cleaner to see and avoid driving straight into walls and other obstacles. Further, the robotic vacuum cleaners must typically be complemented with additional sensors, such as stair sensors, wall-tracking sensors and various transponders to perform accurately. Such sensors are expensive and affect the reliability of the robot. Another way may be to install boundary or perimeter markers as it is known from robotic lawnmowers. This is however cumbersome and requires some time from the user prior to using the robotic vacuum cleaner.
A large number of prior art robotic vacuum cleaners use a technology referred to as Simultaneous Localization and Mapping (SLAM). SLAM is concerned with the problem of building a map of an unknown environment by a mobile robotic vacuum cleaner while at the same time navigating the environment using the map. This is in some cases combined with a horizontal scanning laser for range measurement. Further, odometry is used to provide an approximate position of the robot as measured by the movement of the wheels of the robot. SLAM and odometry in combination result in a cumbersome and long process for the robotic vacuum cleaner to adapt and learn the room or area it is operating in. Thus the first few cleaning processes may take a long time comprising quite some inefficiencies such as driving from one edge of the room to another edge without much of a plan how the cleaning process should be done. In addition double cleaning moves, which means that certain regions are cleaned twice during the same cleaning process, may occur.
US 2002/0091466 discloses a mobile robot with a first camera directed toward the ceiling of a room for recognizing a base mark on the ceiling and a line laser for emitting a linear light beam toward an obstacle, a second camera for recognizing a reflective linear light beam from the obstacle. The line laser emits a beam in the form of straight line extending horizontally in front of the mobile robot.
The use of a base mark on the ceiling and markers on the ceiling in general poses certain disadvantages. First, the robot will need to have two cameras with at least one camera “looking” up towards the ceiling and another camera looking in the direction of movement and thus in the direction of the laser beams from the horizontal line laser. This is expensive and complicates the build up of the robot.
Further, the user has to position at least one base mark on the ceiling by using a chair or ladder.
In addition the robot disclosed in US 2002/0091466 uses the base mark on the ceiling for determining its location and thus for the mapping and it requires the help of the ceiling marker to achieve an effective cleaning pattern and an effective cleaning process. In addition in case the room or area is large, the user may have to install more than one base mark on the ceiling so that the robot does not get lost.
The robot described in the above mentioned prior art is thus not as autonomous as it could be and it has at least the mentioned disadvantages.